Imaging intracellular infections by a fatal fungal pathogen

Project completed 2015.

Professor Robin May, School of Biosciences
Professor Peter Tino, School of Computer Science
Dr Iain Styles, School of Computer Science

Project Aims

1. To develop a computational model for image formation using differential interference contrast (DIC) microscopy, allowing automated analysis of phagosome movement in time-lapse movies.

2. To demonstrate that this can characterize patterns of phagosome change (growth, shrinkage, velocity, etc.) that are predictive of fungal escape

4. To combine high-throughput automated imaging with a drug redeployment library in order to identify lead compounds for modifying cryptococcal behaviour in host cells

This project combines cell culture and live imaging (Biosciences), image formation modeling (Physical Sciences) using state-of-the-art computational techniques (Computer Sciences) to provide a powerful system with which to screen chemical compound libraries.